Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Hold On! Your Emotion and Behaviour when Falling for Fake News in Social Media

Version 1 : Received: 12 May 2021 / Approved: 20 May 2021 / Online: 20 May 2021 (10:29:52 CEST)

How to cite: Vatsalan, D.; Arachchilage, N. A. G. Hold On! Your Emotion and Behaviour when Falling for Fake News in Social Media. Preprints 2021, 2021050477. https://doi.org/10.20944/preprints202105.0477.v1 Vatsalan, D.; Arachchilage, N. A. G. Hold On! Your Emotion and Behaviour when Falling for Fake News in Social Media. Preprints 2021, 2021050477. https://doi.org/10.20944/preprints202105.0477.v1

Abstract

Researchers are concerned about the impact of fake news on democracy, while it could also escalate to life-threatening problems. Fake news continues to spread, so does people's behaviour and emotions about fake news via social media. This opens up the back door for cyber-criminals to entice people (i.e. taking advantage of victims' emotional and behavioural aspects) to click on fraudulent links (e.g. phishing links) associated with fake news when reading. Therefore, we investigate how people's emotional and behavioural features influence reading and diffusing fake news on social media. We proposed a classification model incorporating people's behavioural features and their emotions to better detect fake news in social media. Our results reveal that fake news has more negative emotions than legitimate ones and both title and the content of the news/posts are equally important. Furthermore, we have identified that there exist strong correlations between some of the behavioural and emotional features. Finally, we concluded that emotional and behavioural features are important for fake news classifications as they improve the accuracy of detecting fake news, and the findings of our study can ultimately be used to develop a risk score prediction model for fake news in social media.

Keywords

emotions; sentiment analysis; machine learning; fake news; disinformation

Subject

Computer Science and Mathematics, Algebra and Number Theory

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